Molecules and Cells

Korean Society for Molecular and Cellular Biology (한국분자세포생물학회)
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Identification of Protein Markers Specific for Papillary Renal Cell Carcinoma Using Imaging Mass Spectrometry

  • Na, Chan Hyun (Department of Applied Chemistry, College of Applied Sciences, Kyung Hee University) ;
  • Hong, Ji Hye (Department of Applied Chemistry, College of Applied Sciences, Kyung Hee University) ;
  • Kim, Wan Sup (Department of Pathology, Konkuk University School of Medicine) ;
  • Shanta, Selina Rahman (Department of Applied Chemistry, College of Applied Sciences, Kyung Hee University) ;
  • Bang, Joo Yong (Department of Applied Chemistry, College of Applied Sciences, Kyung Hee University) ;
  • Park, Dongmin (National Cancer Center) ;
  • Kim, Hark Kyun (National Cancer Center) ;
  • Kim, Kwang Pyo (Department of Applied Chemistry, College of Applied Sciences, Kyung Hee University)
  • Received : 2015.01.19
  • Accepted : 2015.04.03
  • Published : 2015.07.31
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Abstract

Since the emergence of proteomics methods, many proteins specific for renal cell carcinoma (RCC) have been identified. Despite their usefulness for the specific diagnosis of RCC, such proteins do not provide spatial information on the diseased tissue. Therefore, the identification of cancer-specific proteins that include information on their specific location is needed. Recently, matrix-assisted laser desorption ionization (MALDI) mass spectrometry (MS) based imaging mass spectrometry (IMS) has emerged as a new tool for the analysis of spatial distribution as well as identification of either proteins or small molecules in tissues. In this report, surgical tissue sections of papillary RCC were analyzed using MALDI-IMS. Statistical analysis revealed several discriminative cancer-specific m/z-species between normal and diseased tissues. Among these m/z-species, two particular proteins, S100A11 and ferritin light chain, which are specific for papillary RCC cancer regions, were successfully identified using LC-MS/MS following protein extraction from independent RCC samples. The expressions of S100A11 and ferritin light chain were further validated by immunohistochemistry of human tissues and tissue microarrays (TMAs) of RCC. In conclusion, MALDI-IMS followed by LC-MS/MS analysis in human tissue identified that S100A11 and ferritin light chain are differentially expressed proteins in papillary RCC cancer regions.

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References

  1. Andersson, M., Groseclose, M.R., Deutch, A.Y., and Caprioli, R.M. (2008). Imaging mass spectrometry of proteins and peptides: 3D volume reconstruction. Nat. Methods 5, 101-108. https://doi.org/10.1038/nmeth1145
  2. Bosso, N., Chinello, C., Picozzi, S.C., Gianazza, E., Mainini, V., Galbusera, C., Raimondo, F., Perego, R., Casellato, S., Rocco, F., et al. (2008). Human urine biomarkers of renal cell carcinoma evaluated by ClinProt. Proteomics Clin. Appl. 2, 1036-1046. https://doi.org/10.1002/prca.200780139
  3. Chaurand, P., Schwartz, S.A., and Caprioli, R.M. (2002). Imaging mass spectrometry: a new tool to investigate the spatial organization of peptides and proteins in mammalian tissue sections. Curr. Opin. Chem. Biol. 6, 676-681. https://doi.org/10.1016/S1367-5931(02)00370-8
  4. Chaurand, P., Schwartz, S.A., Reyzer, M.L., and Caprioli, R.M. (2005). Imaging mass spectrometry: principles and potentials. Toxicol. Pathol. 33, 92-101. https://doi.org/10.1080/01926230590881862
  5. Chaurand, P., Norris, J.L., Cornett, D.S., Mobley, J.A., and Caprioli, R.M. (2006). New developments in profiling and imaging of proteins from tissue sections by MALDI mass spectrometry. J. Proteome Res. 5, 2889-2900. https://doi.org/10.1021/pr060346u
  6. Essen, A., Ozen, H., Ayhan, A., Ergen, A., Tasar, C., and Remzi, F. (1991). Serum ferritin: a tumor marker for renal cell carcinoma. J. Urol. 145, 1134-1137. https://doi.org/10.1016/S0022-5347(17)38555-5
  7. Francese, S., Dani, F.R., Traldi, P., Mastrobuoni, G., Pieraccini, G., and Moneti, G. (2009). MALDI mass spectrometry imaging, from its origins up to today: the state of the art. Comb. Chem. High Throughput Screen 12, 156-174. https://doi.org/10.2174/138620709787315454
  8. Fuhrman, S.A., Lasky, L.C., and Limas, C. (1982). Prognostic significance of morphologic parameters in renal cell carcinoma. Am. J. Surg. Pathol. 6, 655-663. https://doi.org/10.1097/00000478-198210000-00007
  9. Kanamori, T., Takakura, K., Mandai, M., Kariya, M., Fukuhara, K., Sakaguchi, M., Huh, N.H., Saito, K., Sakurai, T., Fujita, J., et al. (2004). Increased expression of calcium-binding protein S100 in human uterine smooth muscle tumours. Mol. Hum. Reprod.10, 735-742. https://doi.org/10.1093/molehr/gah100
  10. Keller, A., Nesvizhskii, A.I., Kolker, E., and Aebersold, R. (2002). Empirical statistical model to estimate the accuracy of peptide identifications made by MS/MS and database search. Anal. Chem. 74, 5383-5392. https://doi.org/10.1021/ac025747h
  11. Kirkali, Z., Guzelsoy, M., Mungan, M.U., Kirkali, G., and Yorukoglu, K. (1999). Serum ferritin as a clinical marker for renal cell carcinoma: influence of tumor size and volume. Urol. Int. 62, 21-25. https://doi.org/10.1159/000030349
  12. Ljungberg, B. (2004). Prognostic factors in renal cell carcinoma. Scand. J. Surg. 93, 118-125. https://doi.org/10.1177/145749690409300206
  13. Miyata, Y., Koga, S., Nishikido, M., Hayashi, T., and Kanetake, H. (2001). Relationship between serum ferritin levels and tumour status in patients with renal cell carcinoma. BJU Int. 88, 974-977.
  14. Morgan, T.M., Seeley, E.H., Fadare, O., Caprioli, R.M., and Clark, P.E. (2013). Imaging the clear cell renal cell carcinoma proteome. J. Urol. 189, 1097-1103. https://doi.org/10.1016/j.juro.2012.09.074
  15. Motzer, R.J., Bander, N.H., and Nanus, D.M. (1996). Renal-cell carcinoma. N Engl. J. Med. 335, 865-875. https://doi.org/10.1056/NEJM199609193351207
  16. Ohuchida, K., Mizumoto, K., Ohhashi, S., Yamaguchi, H., Konomi, H., Nagai, E., Yamaguchi, K., Tsuneyoshi, M., and Tanaka, M. (2006). S100A11, a putative tumor suppressor gene, is overexpressed in pancreatic carcinogenesis. Clin. Cancer Res. 12, 5417-5422. https://doi.org/10.1158/1078-0432.CCR-06-0222
  17. Ozen, H., Uygur, C., Sahin, A., Tekgul, S., Ergen, A., and Remzi, D. (1995). Clinical significance of serum ferritin in patients with renal cell carcinoma. Urology 46, 494-498. https://doi.org/10.1016/S0090-4295(99)80261-1
  18. Rehman, I., Azzouzi, A.R., Cross, S.S., Deloulme, J.C., Catto, J.W., Wylde, N., Larre, S., Champigneuille, J., and Hamdy, F.C. (2004). Dysregulated expression of S100A11 (calgizzarin) in prostate cancer and precursor lesions. Hum. Pathol. 35, 1385-1391. https://doi.org/10.1016/j.humpath.2004.07.015
  19. Rocca, P.C., Brunelli, M., Gobbo, S., Eccher, A., Bragantini, E., Mina, M.M., Ficarra, V., Zattoni, F., Zamo, A., Pea, M., et al. (2007). Diagnostic utility of S100A1 expression in renal cell neoplasms: an immunohistochemical and quantitative RT-PCR study. Mod. Pathol. 20, 722-728. https://doi.org/10.1038/modpathol.3800828
  20. Seliger, B., Dressler, S.P., Lichtenfels, R., and Kellner, R. (2007). Candidate biomarkers in renal cell carcinoma. Proteomics 7, 4601-4612. https://doi.org/10.1002/pmic.200700415
  21. Singh, K.J., Singh, S.K., Suri, A., Vijjan, V., Goswami, A.K., and Khullar, M. (2005). Serum ferritin in renal cell carcinoma: effect of tumor size, volume grade, and stage. Indian J. Cancer 42, 197-200.
  22. Siu, K.W., DeSouza, L.V., Scorilas, A., Romaschin, A.D., Honey, R.J., Stewart, R., Pace, K., Youssef, Y., Chow, T.F., and Yousef, G.M. (2009). Differential protein expressions in renal cell carcinoma: new biomarker discovery by mass spectrometry. J. Proteome Res. 8, 3797-3807. https://doi.org/10.1021/pr800389e
  23. Steurer, S., Seddiqi, A.S., Singer, J.M., Bahar, A.S., Eichelberg, C., Rink, M., Dahlem, R., Huland, H., Sauter, G., Simon, R., et al. (2014). MALDI imaging on tissue microarrays identifies molecular features associated with renal cell cancer phenotype. Anticancer Res. 34, 2255-2261.
  24. Stoeckli, M., Chaurand, P., Hallahan, D.E., and Caprioli, R.M. (2001). Imaging mass spectrometry: a new technology for the analysis of protein expression in mammalian tissues. Nat. Med. 7, 493-496. https://doi.org/10.1038/86573
  25. Stulik, J., Koupilova, K., Osterreicher, J., Knizek, J., Macela, A., Bures, J., Jandik, P., Langr, F., Dedic, K., and Jungblut, P.R. (1999). Protein abundance alterations in matched sets of macroscopically normal colon mucosa and colorectal carcinoma. Electrophoresis 20, 3638-3646. https://doi.org/10.1002/(SICI)1522-2683(19991201)20:18<3638::AID-ELPS3638>3.0.CO;2-W
  26. Torres-Cabala, C., Panizo-Santos, A., Krutzsch, H.C., Barazi, H., Namba, M., Sakaguchi, M., Roberts, D.D., and Merino, M.J. (2004). Differential expression of S100C in thyroid lesions. Int. J. Surg. Pathol. 12, 107-115. https://doi.org/10.1177/106689690401200203
  27. Tyszkiewicz, T., Jarzab, M., Szymczyk, C., Kowal, M., Krajewska, J., Jaworska, M., Fraczek, M., Krajewska, A., Hadas, E., Swierniak, M., et al. (2014). Epidermal differentiation complex (locus 1q21) gene expression in head and neck cancer and normal mucosa. Folia Histochem. Cytobiol. 52, 79-89. https://doi.org/10.5603/FHC.2014.0018
  28. Unwin, R.D., Craven, R.A., Harnden, P., Hanrahan, S., Totty, N., Knowles, M., Eardley, I., Selby, P.J., and Banks, R.E. (2003). Proteomic changes in renal cancer and co-ordinate demonstration of both the glycolytic and mitochondrial aspects of the Warburg effect. Proteomics 3, 1620-1632. https://doi.org/10.1002/pmic.200300464
  29. Wang, G., Wang, X., Wang, S., Song, H., Sun, H., Yuan, W., Cao, B., Bai, J., and Fu, S. (2008). Colorectal cancer progression correlates with upregulation of S100A11 expression in tumor tissues. Int. J. Colorectal. Dis. 23, 675-682. https://doi.org/10.1007/s00384-008-0464-6
  30. Yang, H., Zhao, K., Yu, Q., Wang, X., Song, Y., and Li, R. (2012). Evaluation of plasma and tissue S100A4 protein and mRNA levels as potential markers of metastasis and prognosis in clear cell renal cell carcinoma. J. Int. Med. Res. 40, 475-485. https://doi.org/10.1177/147323001204000209

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